The debate about the impact of automation on the labour market has been ongoing for several years, as new technologies are taking over jobs currently performed by workers. Our study discusses how workers are responding to the growing automation of production processes, and why human capital adjustments are crucial for the workforce to remain competitive in the labour market also in future.
Industrial robots are among the leading automation technologies of the last decades. The International Federation of Robotics (IFR) defines them as “automatically controlled, reprogrammable, multipurpose manipulators, programmable in three or more axes”, and estimates that the global stock of robots has increased from 500 thousand to almost three million units between the early 1990s and the late 2010s.
An Uber driver once told me he keeps a gun under his seat because “Uber doesn’t have my back”. Another was told by a customer that he should “go back to his own country”. Yet another was punched in the back of his head while driving.
Anyone who has ever worked a customer service job knows that customer abuse against workers is rampant; one study found that, on average, call center workers interact with abusive customers more than ten times a day. The gig economy is no exception.
Yet if platform workers are “their own boss”, why are they subjected to constant customer abuse? And why does this issue seem to be getting worse over time?
The COVID-19 pandemic sent large numbers of workers whose jobs permitted it into working from home. At the peak more than 60% of U.S. workers worked remotely. Working from home blurs the boundaries between work and personal lives. We find, surprisingly, that remote work brought with it both more and fewer hours, but this varied depending on family care responsibilities as well as gender, race, and class.
Work hours are important because working time is a fundamental aspect of working conditions associated with pay and status, family and personal lives, as well as health and well-being. Given the currently “frighteningly high levels” of burnout among U.S. workers, it becomes all the more important to understand how working from home affects hours worked.
In a recently published study, we investigate how work hours changed as women and men moved to remote working conditions, and how remote workers themselves account for increases, decreases, or stability in their work hours. We find different experiences for women and men, as well as at the intersections of gender with caregiving obligations, race/ethnicity, and socioeconomic status.
By many accounts, women self-select out of STEM programs at various points across the career trajectory because they feel they do not belong, or because they feel less confident in their ability to thrive in a STEM career. When speaking of issues related to gender inequality in STEM, the predominant metaphor used is that of a “leaky pipeline.”
Last year, we completed a report for a scientific governing body on ways they can make their funding services to university faculty more equitable. We interviewed women who opted out of academic careers because the culture in their labs was inhospitable. And we documented stories of interviewees’ colleagues who experienced harassment and likewise opted out of academia.
Taken together, we were provided evidence of a leaky pipeline, and we had conversations with interview participants about what might ultimately be its cause. These conversations were unsettling and unsatisfactory because we kept butting against the issue of recruitment, hiring, and retention. But the real problem with the leaky pipeline explanation of gender inequality is the metaphor itself.